High-precision near-land aircraft navigation system

ABSTRACT

An aircraft including an approach and landing system, including a navigation unit for providing navigation information, a weather radar unit for providing radar information, a processor which receives navigation information from the navigation unit and information from the weather radar unit, the processor unit providing an output representing information concerning the aircraft in accordance with the provided navigation information and radar information, a memory for storing information representing a scene, the processor unit correlating the stored scene information with the output representing information concerning the aircraft to provide a mapped scene, a display unit for displaying the output of said processor and the mapped scene, and a steppable frequency oscillator for providing a signal which is stepped in frequency to the weather radar unit, thereby providing an increased range resolution.

This is a continuation of Application Ser. No. 08/251,451 filed May 31,1994, now U.S. Pat. No. 5,654,890.

FIELD OF THE INVENTION

The present invention is directed to an autonomous precision approachand landing system (APALS) for enabling low visibility landings atairports.

BACKGROUND OF THE INVENTION

Current industry practice for low-visibility landings is dependent onairport ground equipment and inertial navigation equipment. Thesetechniques are limited to landings at those runways which are equippedwith highly reliable transmitters of radio frequency localizer and glideslope information. These existing systems either land the aircraft usingan automatic pilot or aid the pilot in landing the aircraft by providingthe pilot with autopilot control commands displayed on a Head Up Display(HUD).

It has been suggested that future systems make use of informationreceived from the Global Positioning System (GPS) in conjunction withon-board Inertial Navigation systems (INS) to generate the necessaryprecise navigation for landing. However, in addition to the externalsatellites required for GPS, these systems are currently envisioned torequire ground stations at known locations near the runway for thedifferential precision necessary for landing. Other proposed systemsprovide the pilot with a real time image of the runway scene as derivedfrom millimeter wave (MMW), X-Band, or infrared (IR) frequencies.

The following are further examples of navigation systems known in theart.

U.S. Pat. No. 5,136,297 to Lux et al discloses an autonomous landingsystem. The Lux patent includes a navigation unit employed in the systemwhich includes a sensor, flight position data, an image correction unit,a segmentation unit, a feature extraction unit and a comparison unit.The Lux patent discloses that a comparison is conducted as to whether ornot a sequence of features in the overflight path image pattern agreeswith features found in a reference store, such as map data which isstored in the system. Further, Lux discloses the use of a radarnavigation system for use as a sensor in the system.

U.S. Pat. No. 4,698,635 to Hilton et al discloses a radar guidancesystem coupled to an inertial navigation apparatus. The system includesa master processor, a radar altimeter, a video processor, a memory and aclock. The memory has stored therein cartographic map data.

U.S. Pat. No. 4,495,580 to Keearns is cited to show a navigation systemincluding a radar terrain sensor and a reference map storage device forstoring data representing a terrain elevation map.

U.S. Pat. No. 4,910,674 to Lerche discloses a navigation method whichincludes a correlator for comparing terrain reference data withprocessed altitude data obtained with a wave sensor.

U.S. Pat. No. 4,914,734 to Love et al is cited to show a map-matchingaircraft navigation system which provides navigational updates to anaircraft by correlating sensed map data with stored reference map data.

U.S. Pat. No. 4,891,762 to Chotiros is cited to show a patternrecognition system for use in an autonomous navigation system.

The above-mentioned prior systems suffer from one or more of thefollowing problems:

1) Reliance on ground-based systems for precise terminal landinginformation severely reduces the number of runways available for Cat IIIa and b landings (currently 38 runways in the U.S.).

2) Reliance on GPS and differential ground transmitters for GPS createsa need for currently rare ground equipment and a lack of reliability(based on the military nature of GPS). The GPS is a military programowned, operated, and paid for by the United States Air Force originallyintended for military navigational purposes and is designed so thatcivilian use can be made of it but at a reduced accuracy. The militaryuses a very special code which gives them better accuracy, that iscalled the P code. The normal civilian code is called the C code whichis good to about 30 m in accuracy; however, the military retains theright to disable the C code to the point where the accuracy goes down toabout no better 100 m. This is what the military refers to as "selectiveavailability" so that in time of conflict they can turn on selectiveavailability and deny the enemy the ability to navigate better than 100m. There are a number of schemes for getting around the inaccuraciesimposed by the military. However, the Air Force has maintained aposition that they are against any of these schemes which improve theaccuracy when they are trying to make it inaccurate.

The lack of reliability is also a result of the fact that, in order tobe accurate, at least four satellites must be present in the overheadview; and, if one of the four satellites fails, then the accuracy willbe degraded. Thus, the reliability is not just based on the on-boardequipment, i.e., the GPS receiver, but it is also based on thereliability of the satellites themselves.

3) Additional sensors, such as MMW and IR, currently envisioned forsystems to provide pilots with the "situational awareness" necessary tosuccessfully land in low visibility conditions are expensive additionsto the on-board flight equipment and are marginal in performance. MMWreal-beam radars provide "grainy" low resolution images which aredifficult to interpret and IR systems cannot penetrate in many types offog that cause the "low visibility" in the first place.

SUMMARY OF THE INVENTION

It is therefore an object of the present invention to overcome theproblems associated with the prior approach and landing systems.

It is another object of the invention to provide an approach and landingsystem which provides low visibility take-off and landing assistance forseveral classes of aircraft.

It is another object of the invention to provide safe landing of generalaviation and transport aircraft (covered by parts 25, 91, 121 and 125 inthe Code of Federal Regulation) in low visibility conditions [CategoryII, IIIa, and IIIb defined by the Federal Aviation Administration (FAA)]without dependence on high reliability ground transmitting equipment.

These and other objects are accomplished by the present invention whichprovides an Autonomous Precision Approach & Landing System that makesuse of radar echoes from ground terrain and cultural (man made) targetsto provide the on-board Inertial Navigation System with accurateaircraft position and velocity updates. According to the invention,these measurements come from a modified standard X-band, low-resolutionweather radar.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of the APALS system according to theinvention.

FIG. 2 is a waveform diagram according to the invention.

FIG. 3 is a circuit diagram of a modified weather radar device accordingto the invention.

FIGS. 4(a)-4(e) illustrate steps of APALS Synthetic Aperture Radar (SAR)processing according to the invention.

FIG. 5 shows a reference scene and a corresponding Radar Map accordingto the present invention.

FIG. 6 illustrates a Generalized Hough Transform Map-Match Algorithmemployed in the present invention.

FIG. 7 illustrates a Navigation Solution according to an example of theinvention.

FIG. 8 illustrates a Head-up Display (HUD) according to the presentinvention.

DETAILED DESCRIPTION OF A PREFERRED EMBODIMENT

Several of the important features of the APALS system according to theinvention are set forth below:

A. Modified Weather Radar: The modification to a conventional weatherradar allows the modified weather radar to make high resolutionsynthetic aperture maps of overflown terrain.

B. Area Correlation: This refers to the application of matchingsynthetic aperture radar maps with previously stored references tolocate specific spots on the ground near a path to a specific runway.

C. Range/Range Rate Measurements Integrated Into Kalman Filter: Thisrefers to the application of using high resolution radar range andvelocity measurements of specific, but not augmented, spots on theground of known location to update a navigation system using Kalmanfiltering.

D. Situational Awareness Display Format: This refers to the applicationof precise navigational information to provide the pilot with a"situational awareness" display of sufficient accuracy to allow thepilot to land the aircraft in low visibility conditions in the samemanner as if (s)he were using his/her judgement to land the plane ingood visibility conditions.

Each of the above features is discussed in detail below.

FIG. 1 is a block diagram of the APALS system according to the presentinvention. The other NAV Aids 2 refers to the navigation aids that areconventionally employed on any aircraft and include, for example, a VOR(VHF omnidirectional radar), DME (distance measuring equipment)receiving equipment, the artificial horizon, the vertical gyro, theairspeed indicator, and the altimeter (which is a barometric altimeter).The APALS processor 16 will make use of this information in order tomonitor the reasonableness of the APALS estimate concerning the state ofthe vehicle, which is the output X from the processor 16. Theabove-discussed elements all interface to the system over a standardinterface bus such as the known ARINC 429 bus.

The INS (inertial navigation system) or IMU (inertial measurement unit)4 are inertial instruments that measure the translational accelerationsand the angular rates. There are several different IMU's that can beemployed in APALS, one of which is, for example, a Bendix unit known asthe Bendix mini-tact IMU.

The GPS receiver 6 is a special receiver that is designated to receivethe satellite signals and deduce from those satellite signals theposition and velocity of the aircraft. There are several models that canbe used for this, but there is only one or two at present that havepassed the FAA requirements for primary navigation equipment on-board anaircraft.

The weather radar 8 which is also equipment that will already beon-board the aircraft is, according to the invention, as will bediscussed below modified. For example, the Honeywell Primus 870 made byHoneywell may be employed. This radar is a non-coherent radar so itwould have to be modified with a new receiver and transmitter to make itcoherent. The weather radar 8 provides a range R, and range rate R'outputs to the Processor. The weather radar 8 receives a radar frequencycontrol signal from the Processor 16 which will be discussed below inconnection with the radar modification shown in FIG. 3.

The scene data base 10 is a data base created by going to differentairports that will use the system and making flights during which theradar signatures of the ground returns are measured. Further, aerialphotographs are taken to use together with the radar data to makereferences which would then be used to compare against the radar returnsthat will occur when the actual low visibility landing is taking place.

The display generator 12 and the display 14 are typically supplied bythe manufacturer of the device known as a Head-Up Display (HUD), whichis what the APALS uses as a see through device that allows the pilot toview the outside world, and see the APALS display in front of him orher. The pilot will see a virtual runway even when the actual runway isobscured by, for example, clouds or fog. Suitable HUD's are currentlybuilt by GEC Avionics (Great Britain), Flight Dynamics, Inc. (Portland,Oreg.) and Sextant Avionique (France). The actual APALS output is avector labeled X and consists of the position, velocity and attitudeinformation of the aircraft as best determined by the APALS system. Thedisplay generator typically takes that information and generates whatthe outside world scene would look like from the currently estimatedstate of the aircraft, X.

The processor 16 receives inputs from elements 2, 4, 6, 8 and 10 andoutputs vector X. There are a number of known processors that can beused for APALS.

A. Modified Weather Radar

The radar modification consists of applying randomized stepped frequencypulse compression to allow a range resolution of 4 meters (even though apulse length of 2 μsec would normally limit range resolution to 300meters). The waveform consists of a series of pulses at the normalhigher Pulse Repetition Frequency (PRF) of the weather radar (˜3000 Hz).The first 160 pulses are randomly stepped in frequency so that eachpulse is at a different frequency. Any one pulse, however, stays at aconstant frequency for its entire 2 μs duration. This is importantbecause it allows the precision measurements to be made withoutmodifying the band-pass characteristics of the radar receiver. Thefrequencies are such that there are 160 different frequencies spanning40 Mhz in 250 Khz steps. Over the time of each set of 160 pulses, the 40Mhz spectrum is completely filled. The order of the steps is randomizedto avoid ambiguities. A diagram of the waveform is shown in FIG. 2. Thestep size is 250 Khz which corresponds to a 4 μs or 600 meter "coarse"range bin. This wider (than 2 μs) coarse bin was chosen to eliminate anyambiguities from adjacent pulse "spillover" energy. The waveform can beas long as necessary to integrate returns for a precise Dopplermeasurement.

The waveform is extended to multiples of 160 pulses because 160 is thenumber of pulses required to cover the 40 MHz bandwidth needed for 4meters range resolution. In this case the integration time is limited to0.25 seconds since, at X-band, it will yield a velocity resolution of0.07 m/sec. which is a sufficient accuracy to update the navigationKalman filter.

FIG. 3 shows a typical implementation of generating the waveform byadding a steppable frequency oscillator 17 to the weather radar. Asshown in FIG. 3, the majority of the circuits of radar (transmitter 18,frequency multipliers, dividers and mixers 20, receiver 22, duplexer 24)remain unchanged. The integration of the modified waveform into theweather radar from each of the different radar manufacturers will beunique.

Processing the waveform to achieve the desired resolution (4 m in rangeand 0.07 m/sec. in Doppler) is accomplished in a highly efficient mannerbecause the image is being taken of just one short segment of range(where the beam intersects the ground). The "picture" or map will extend160 meters or 40 pixels in range and therefore is contained in one 600meter "coarse range". This is in effect "zoom processing" of the regionwhich is very efficient. The application of zoom processing to thisunique waveform allows very high resolution to be achieved with veryminor physical modifications to a normally low resolution radar.

Motion Compensation: The Synthetic Aperture Radar (SAR) map that isrequired for this system to work well covers a small area and theaccuracy of the vehicle motion required is within the bounds of theknowledge of the system. This is because the navigation portion of thesystem will have very precise knowledge of the state of the vehicle'smotion relative to the earth as will be discussed below.

The following delineates the steps required for the two dimensional zoomprocessing of APALS.

As described in the waveform of FIG. 2, during the integration of 0.25seconds there are 4000 pulses. This large integration time is brokendown into 25 sub-intervals or "words" of 160 pulses each (FIG. 2).During each sub-interval, the full bandwidth of 40 MHz is transmitted byhaving each pulse at a different frequency taken, at random, from a setof 160 frequencies spaced 250 KHz apart. If the lowest frequency were 9GHz, the sequence of frequencies would be: 9.000 GHZ, 9.00025 GHz, 9.005GHz, 9.00075 GHz, 9001 GHz . . . 9.040 GHz. The order is scrambledrandomly for reasons which will be explained below.

FIG. 4(a) is a wave diagram for explaining a coarse range bin. With a 2μs pulse (1), if the receive signal (2) and (3) is sampled the same timedelay after the transmit pulse, those returns will all represent targetsor ground clutter from the same range. Since the pulse is 2 μs wide, theenergy at the time of the sample will come from 150 meters in front ofto 150 meters behind the point on the ground with a time delay of thesample center. The processing chosen covers a 600 meter region centeredat the time of the central return. While there should be no return inany area beyond ±150 meters, there may be spill-over from other brightreflectors and by processing the wider coarse bin, the possibility ofambiguous foldover is eliminated.

To simplify the explanation, a "linear" rather than a random frequencysequence is examined. In FIG. 4(b) it is seen that the samples, eachbeing from a different pulse in the chain of 4000 pulses, range infrequency from f₁ to f₁₆₀ and then f₁ to f₁₆₀ is repeated for the next160 Pulse Repetition Intervals (PRI's) and so on for 25 sub-intervalsuntil 4000 pulses have been transmitted and 4000 receive samples havebeen gathered. As shown from FIG. 4(b), processing the 4000 samples intoa range profile of fine 4 meter bins is nothing more than summing thesample values that come from the same frequency (there are 25 of them)and using the sum as one of the inputs to an Inverse Digital FourierTransform (IDFT), and representing that process for all 160 frequencies.A Fourier transform is a process of taking samples in time of a waveformand determining how much energy there is at each frequency and theinverse of the process is taking samples of energy content at differentfrequencies and producing what the waveform looks like as a function oftime (time is equivalent to range for a radar echo).

The example given above and in FIG. 4(b) is a simplification that wouldwork well if there were no motion between the radar and ground. In orderto describe what is necessary for APALS to accommodate motion, it isnecessary to introduce the concepts of phase and phase compensation.

The phase of a radar signal depends on two items, the frequency orwavelength of the signal and the distance from the transmitter. This isshown in FIG. 4(c). Radar waves are variations in local electric andmagnetic fields which can be represented by the sine wave shown in FIG.4(c).

The distance from one peak to another is called the wavelength and isdetermined by the frequency of the transmitted signal. FIG. 4(c) shows aReceiving Object whose distance is 51/4 wavelengths away from theTransmitter. The whole number of wavelengths is not important to phasebut the remainder or fractional part is the phase difference betweenwhat is sent and what is received. In FIG. 4(c), the phase difference is1/4 of one wavelength or 90° (one wavelength is characterized by onefull cycle of 360°). If the receiving object simply reflected the signalback to a Receiver co-located with the transmitter, as is the case withradar, the distance and, therefore, the phase shift is doubled to 180°.

The phase of the returns from different samples but off of the samestationary object will change with a frequency hopped radar such asAPALS. FIG. 4(d) shows the effect of changing wavelength on phase. InFIG. 4(d), even though the transmitter and the receiving object are thesame distance apart as they are in FIG. 4(c), the phase has increased to180°, one way. In FIG. 4(d) there are 51/2 wavelengths in the singlepath-length.

As the frequency of the pulses increases (FIG. 4(b)), the wavelengthgets shorter and the phase difference increases. It is precisely thischange in phase as a function of frequency that allows the IDFT todiscern the ranges of object from the frequency content of the returnsamples. The samples, by their nature, contain both a measure of theenergy and a measure of the phase difference of the return from a pulseof a particular frequency.

Relative motion between the Transmitter and the Reflecting Object causesa phase shift with time which causes a phase shift from pulse to pulseas shown in FIG. 4(e).

This phase shift as a function of time is known as the Doppler effect.The measurement of this rate of change of phase or Doppler is whatallows APALS to update range rate as well as range for the inertialsystem after each map-match. It is also what creates the need for phasecompensation.

It is important to note that the phase changes due to increasingfrequency have the same characteristic as the phase changes due toincreasing distance between the transmitter and the reflecting object.In both cases, the phase changes will increase steadily with time. Thisis the ambiguity that was mentioned earlier. As long as the frequenciesare stepped in order from pulse to pulse, the IDFT will not be able todistinguish between distance of the Reflecting Object and the speed ofthe Reflecting Object. This is because the distance information iscontained in the phase differences of the reflections off a singleobject at different transmit frequencies.

To obviate this ambiguity problem, the frequencies are not stepped inorder of increasing frequency as shown in FIG. 4(b), but ratherrandomly. This breaks the linearity of the phase changes with time dueto frequency shifting so that it can be separated from the always linearchanging phase that is due to constant velocity motion. It is stillnecessary to present the sampled values of the return signal to the IDFTin order of increasing frequency so the order of frequencies transmittedmust be kept track of. This is accomplished in APALS by using apre-stored pseudo-random frequency order which is 4000 elements long.

Once the relationships between distance, phase, and velocity areunderstood in the context of the APALS waveform as described above, thephase compensation and processing for APALS can be concisely explainedin the following steps:

1) The received waveform is converted to a set of digital samples whichpreserves both signal strength and phase difference. This process iswell known in the art as in-phase and quadrature sampling or I & Qsampling. The digital samples are stored temporarily and tagged bothwith their order in time of reception and with their frequency order.

2) The coarse range of interest is identified by the system based on thedesired map area, and the samples which come from the correspondingdelay are singled out for processing.

3) The Doppler frequencies are determined for the desired map area, andthe center frequencies for the Doppler bins to be processed aredetermined.

4) For each Doppler bin, the set of samples is arranged in order of thetransmit frequency which generated it, and presented for phasecompensation prior to being sent to the IDFT.

5) For each Doppler bin the phase rotation for each transmit frequencyand each receive time is calculated and that phase is subtracted fromeach sample according to its time order and adjusted for its wavelengthbased on its transmitted frequency. The net effect is that motion istaken out of the samples that are moving at the precise velocity that isthe designated center of the Doppler bin or filter. Objects that aremoving faster or slower will not "add up" because the phases of theirsamples will not be recognized by the IDFT.

In order to prevent smearing, due to accelerations which change thevelocity during the 0.25 second dwell, the compensating phase rotationsmust be calculated based, not on a constant velocity, but on a velocitymodified by the aircraft's accelerations. These acceleration values arereadily available in the APALS system because they are part of theaccurate state vector which is calculated by the navigation filter.

B. Area Correlation

The APALS system uses the Scene Data Base 10 for pre-stored scenes asreferences with which to compare the radar maps that are producedthrough the weather radar. The radar maps can be thought of ascomprising resolution "cells" whose dimensions are range resolution inthe down range direction and range rate resolution in the cross rangedimension. Down range direction is simply the radial distance from theaircraft. In a radar system the normal way of mapping with a radar is tocut the return up into pieces that are returns coming from differentranges. This is because the radar is capable of measuring range by thetime delay of the return. The down range dimension is always thedistance radially away from the radar. The present system is typicallylooking at 45° right or left and so the down range dimension is a linegoing 45° off the nose of the aircraft. The cross range dimension is thedimension that is directly orthogonal or at 90° to the down rangedimension. It is not always exactly 90°, in the present system it ismeasured by changes in the doppler frequency of the return. Thefrequency of the return is dependent on the relative velocity in thedirection of that return. The contextual information in the radar map iscompared to that of the reference. When a match is found for each pointof ground represented by a cell in the reference, the range and rangerate of the sensed scene are known with respect to the aircraft. Sincethe location of at least one point in the scene is known precisely withrespect to the desired touch down point, by simple vector subtraction,the range rate to the touch down point is calculated. There are twoaspects to generating this important information:

1) Generating a reference which will allow a locally unique match to theradar map.

2) Using a correlation algorithm that efficiently "fine-tunes" the matchpoint to a 1-cell accuracy and provides a "measure of goodness" orconfidence in the match.

The references for APALS are generated from aerial photographs that havebeen digitized or scanned into a computer and from SAR maps. The SARmaps are taken in two swaths, one on either side of the final approachtrajectory, that are centered 1 mile offset of the aircraft's trajectory(ground projection). Software is used to match points in the aerialphoto with coordinates of a pre-stored navigation grid so that thelocation of any point in the photo is known relative to the runway touchdown point (no matter how far the scene is away from the runway). Thekey features of these references are that they are simple and that theyrely on prominent cultural and natural features which produce consistentradar returns that are distinguishable as lines with a unique shape. Thetwo types of features to have these characteristics consistently are thecorners made by a building face and the ground, and roads.

FIG. 5 shows a typical reference and the corresponding radar map. Inthis case the dots represents a specific pattern of a highway crossing.Such simple references are found to work well when used with the mapmatching algorithm well known in the art as the "generalized Houghtransform" which is described below.

The correlation algorithm used for map matching in the APALS system isthe well known generalized Hough transform. The Hough transform isincorporated in several image processing techniques in use today,especially in military applications. In general, the Hough transform isa computer method typically used to find a line or other simpleshapes/patterns in a complex picture. This scene matching algorithm isadvantageous in that:

a) It requires very few points to be compared, (i.e., much less than thetotal in the scene).

b) It requires the computer to perform only the mathematical operationof adding and avoids the other more time consuming mathematicaloperations.

In FIG. 6(A) a simple reference is shown to the left and a very sparsesensed scene (just two points) is shown to the right. The algorithmworks such that every point in the sensed scene is operated on in thefollowing manner:

1) Each point in the reference is tried as the particular sensed point.

2) As each point in the reference is tried, the position that the"nominated point" (black point in the reference) occupies in the sensedscene is recorded. This is shown in the sequence of scenes in FIG. 6b.After all the points in the reference are used, the set of recorded"nominated" points in the sensed scene is an "upside-down and backwards"replica of the reference scene, rotated about the "nominated point".This reversed image is shown above the last block of FIG. 6b.

3) As all the points in the reference are operated on, the point in thescene with the most accumulated nominations is designated as the matchpoint. This is illustrated in FIG. 6c.

C. Range/Range Measurements Integrated Into Kalman Filter

The measurements being made by the radar are the magnitude of the rangevector and the magnitude of the range-rate vector from the aircraft to aspecific point in the map match scene. If at least three of thesemeasurements were being made simultaneously, one could solve for thethree elements of aircraft velocity explicitly. This solution is shownin FIG. 7. The sequence of measurements being made in FIG. 7 are therange and range-rate to known points on the ground. The way in whichthese are used is exactly analogous to the way the global positioningsystem works with satellite measurements. For example, consider threesatellites that are displaced in the sky angularly. If the range and therange rate to those satellites are known, then the components of boththe position vector and the velocity vector of the position relative tothose three satellites can be solved. Beyond that, it is necessary todepend on information stored on the satellites and transmitted down sothat it can be determined where they are. Then the position can bededuced. The difference in APALS is that the APALS system takes picturesof the actual ground and compare the taken pictures to stored maps. Onceit compares them to stored maps and finds the match point, the matchpoint is immediately known in terms of its range and range rate at thatpoint of time. As APALS progresses it measures its range and range raterelative to known points on the ground. Once it measures three differentpoints, it can form a deterministic solution of where it is, in whatdirection it is heading and how fast it is going. The sequence in APALSis a little different in that it does not obtain a good geometric casein close time proximity. Rather, it flies along mapping from side toside but not getting that third one. It repetitively gets the range andrange rates on each side, and over time forms a very accurate solutioniteratively to the equation that allows it to know its position vectorand velocity vector.

Since however, the measurements being made by radar are separated in itis neas much as 4 seconds, it is necessary to solve for the componentsof the vectors recursively, over time, through the use of a Kalmanstatistical filter. The Kalman filter uses data from an inertialnavigation system INS, or an inertial measurement unit (INU) 4 (FIG. 1)to determine the motion of the aircraft between measurement times. TheINS or IMU 4 is more than just the inertial instruments, but thecomplete collection of inertial instruments and computer that result ina navigation solution including position and velocity. An INS istypically only used on commercial aircraft today that traverse theocean.

D. Situational Awareness Display Format

The raw output of the APALS system is a very accurate estimate of the"state vector" of the aircraft in a coordinate system that has itsorigin at the desired touch down point on the particular runway that istargeted. This knowledge of position, velocity and attitude are providedas a "situational awareness" display which the pilot can effectively useto safely land the aircraft. This is accomplished primarily bydisplaying a conformal, properly positioned runway outline in properperspective to the pilot on a Head-up Display (HUD). In clear weatherthe image will overlay that of the actual runway edges as the pilotviews the runway through the wind screen. The appropriate touch-downzone will also be displayed (conformably), thereby providing the pilotsituational awareness such that (s)he may land his/her aircraft in thesame manner as (s)he would in visual meteorological conditions (VMC).The use of the HUD allows the pilot the earliest possible view of theactual visual scene on the way to touchdown. The precise navigationalknowledge of the APALS system together with the radar altimeter allowsfor the generation of a "flare cue" to tell the pilot when and how toflare for a precise, slow descent-rate touchdown.

The key aspect in being able to land using situational awareness is thedisplay of the conformal runway symbol and extended center-line in acontext which also includes conformal symbols of the horizon line,flight path vector, and 3° glide slope indicator. The display of thesesymbols can be derived from APALS navigation knowledge or from otheraircraft instruments. FIG. 8 shows a particular symbol set with theaddition of the synthetic runway image.

True ground speed information in the APALS system is sufficient togenerate moving segments in the extended center-line to create asensation of "speed" for the pilot.

A secondary aspect of APALS is that the X-band radar together with APALSenhanced resolution can detect runway incursions prior to landing in lowvisibility conditions. This is accomplished with a broad sweeping groundmap just prior to landing which is similar to the "ground map mode" of aconventional weather radar. The notable exception is that the rangeresolution is two orders magnitude sharper than that of the conventionalweather radar. This allows large objects, such as a taxiing aircraft tobe resolved into more than one pixel. As a result, the APALS is able tocorrectly distinguish and separate larger and smaller objects from eachother. When this is coupled with the precise navigational knowledge ofAPALS, any radar returns can be related to their precise location in theairport scene to determine if they are a hazard.

As set forth above, the APALS system does not depend on ground equipmentinstalled at a particular airport. It therefore offers the potential oflow-visibility landings at many airports than are currently unavailablefor such landings because they do not have the ground equipment ofsufficient reliability to support the automatic landing systems.

Further, APALS does not require the addition of any new vision sensorson the aircraft or installations on the ground and thereforeinstallation costs are minimum. The accuracy and reliability of thedisplay can be checked and verified during normal visual operations. Itcan also be routinely used for training at any airport during normalvisual operations. In addition, it can detect runway obstacles prior tolanding without adding any sensors.

The display for APALS can be either head-up or head-down.

The waveform can be varied in PRF (Pulse Repetition Frequency), pulsewidth, bandwidth, and integration time to affect changes in resolutionand processing dynamic range. The Pulse Repetition Frequency is thenumber of pulses per second that the radar transmits. This is importantbecause the PRF determines the amount of average power that the radarreceives. It also determines what kind of ambiguities there are inrange.

Those skilled in the art will understand that variations andmodifications can be made to system described above, and that suchvariations and modifications are within the scope of the invention. Forexample, different scene match correlation algorithms and differentnavigation filters (other than Kalman) such as neural net "intelligent"estimators can be used without changing the nature or concept of thepresent invention.

What is claimed is:
 1. A method of aircraft navigation using radar,comprising:storing information of cultural or natural features in anarea of the ground along and to the sides of a flight path; using saidradar during flight to obtain information of said features along and tothe sides of said flight path; comparing said stored information withsaid information obtained by radar to determine successive differentmatch points representing different ground locations; determining therange and range rate of each of said match points; determining theaircraft's location and velocity based on repetitive range and rangerate measurements of said match points; and supplementing the accuracyof said aircraft location and velocity determination with informationfrom at least one of an additional navigation unit.
 2. The methodaccording to claim 1, wherein said additional navigation unitinformation is based upon integration of inertial measurements.
 3. Themethod according to claim 1, wherein said additional navigation unitinformation represents locations between said match points and iscombined with said aircraft location and velocity determination usingKalman statistical filtering.
 4. The method according to claim 1,wherein a phase changing effect created by motion of said navigationunit is reduced, said method comprising:defining subsets of a frequencyhopped radar signal and a center frequency for each subset, bouncingsaid radar signal off of an object and receiving a reflected version ofsaid signal to determine a phase change in said signal; receivingreflected versions of said subsets, and subtracting phase effects fromthe samples that correspond to the center frequency of said subset. 5.The method of claim 1 wherein phase compensation is provided for saidradar, said method comprising:storing a pseudo-random frequency order;changing a transmission frequency of a radar signal based on saidpseudo-random frequency order; using said pseudo-random frequency orderto sample a received radar signal which is a reflected version of saidtransmitted radar signal, thereby generating samples of said receivedradar signal; and reordering said samples in an order of increasingfrequency.
 6. The method according to claim 5, furthercomprising:summing a group of said samples; and performing an InverseDigital Fourier Transform on said samples to develop a range value. 7.The method according to claim 5, further comprising:tagging saidreceived samples with information of their order of reception and orderof frequency; identifying a coarse range of interest based on aparticular area of the ground; selecting the received samples whichcorrespond to said particular area; defining signal subsets of saidtransmitted signal; determining the Doppler frequencies for saidselected samples and center frequencies for the subsets corresponding tosaid particular area; arranging said received samples in frequency orderwithin said subsets; calculating the phase rotation due to transmitfrequencies and receive times for the received samples, and subtractingsaid phase rotations from the corresponding samples according to thetime order and wavelength of said sample, to thereby reduce effects ofmotion of the navigation unit on the interpretation of the receivedradar signals.
 8. A method of aircraft navigation using radar,comprising:storing information of cultural or natural features in anarea of the ground along and to the sides of a flight path; using saidradar during flight to obtain information of said features along and tothe sides of said flight path; comparing said stored information withsaid information obtained by radar to determine match pointsrepresenting different ground locations; determining the range and rangerate of said match points; and using said range and range rate in thenavigation or state vector measurements of said aircraft.
 9. A methodaccording to claim 8 wherein a phase changing effect created by motionof said navigation unit is reduced, said method comprising:definingsubsets of a frequency hopped radar signal and a center frequency foreach subset, bouncing said radar signal off of an object and receiving areflected version of said signal to determine a phase change in saidsignal; receiving reflected versions of said subsets, and subtractingphase effects from the samples that correspond to the center frequencyof said subset.
 10. The method of claim 8 wherein phase compensation isprovided for said radar, said method comprising:storing a pseudo-randomfrequency order; changing a transmission frequency of a radar signalbased on said pseudo-random frequency order; using said pseudo-randomfrequency order to sample a received radar signal which is a reflectedversion of said transmitted radar signal, thereby generating samples ofsaid received radar signal; and reordering said samples in an order ofincreasing frequency.
 11. The method according to claim 10, furthercomprising:summing a group of said samples; and performing an InverseDigital Fourier Transform on said samples to develop a range value. 12.The method according to claim 10, further comprising:tagging saidreceived samples with information of their order of reception and orderof frequency; identifying a coarse range of interest based on aparticular area of the ground; selecting the received samples whichcorrespond to said particular area; defining signal subsets of saidtransmitted signal; determining the Doppler frequencies for saidselected samples and center frequencies for the subsets corresponding tosaid particular area; arranging said received samples in frequency orderwithin said subsets; calculating the phase rotation due to transmitfrequencies and receive times for the received samples, and subtractingsaid phase rotations from the corresponding samples according to thetime order and wavelength of said sample, to thereby reduce effects ofmotion of the navigation unit on the interpretation of the receivedradar signals.